agsamantha/node_modules/@langchain/community/dist/embeddings/baidu_qianfan.cjs
2024-10-02 15:15:21 -05:00

169 lines
6.7 KiB
JavaScript

"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.BaiduQianfanEmbeddings = void 0;
const embeddings_1 = require("@langchain/core/embeddings");
const chunk_array_1 = require("@langchain/core/utils/chunk_array");
const env_1 = require("@langchain/core/utils/env");
class BaiduQianfanEmbeddings extends embeddings_1.Embeddings {
constructor(fields) {
const fieldsWithDefaults = { maxConcurrency: 2, ...fields };
super(fieldsWithDefaults);
Object.defineProperty(this, "modelName", {
enumerable: true,
configurable: true,
writable: true,
value: "embedding-v1"
});
Object.defineProperty(this, "batchSize", {
enumerable: true,
configurable: true,
writable: true,
value: 16
});
Object.defineProperty(this, "stripNewLines", {
enumerable: true,
configurable: true,
writable: true,
value: true
});
Object.defineProperty(this, "baiduApiKey", {
enumerable: true,
configurable: true,
writable: true,
value: void 0
});
Object.defineProperty(this, "baiduSecretKey", {
enumerable: true,
configurable: true,
writable: true,
value: void 0
});
Object.defineProperty(this, "accessToken", {
enumerable: true,
configurable: true,
writable: true,
value: void 0
});
const baiduApiKey = fieldsWithDefaults?.baiduApiKey ??
(0, env_1.getEnvironmentVariable)("BAIDU_API_KEY");
const baiduSecretKey = fieldsWithDefaults?.baiduSecretKey ??
(0, env_1.getEnvironmentVariable)("BAIDU_SECRET_KEY");
if (!baiduApiKey) {
throw new Error("Baidu API key not found");
}
if (!baiduSecretKey) {
throw new Error("Baidu Secret key not found");
}
this.baiduApiKey = baiduApiKey;
this.baiduSecretKey = baiduSecretKey;
this.modelName = fieldsWithDefaults?.modelName ?? this.modelName;
if (this.modelName === "tao-8k") {
if (fieldsWithDefaults?.batchSize && fieldsWithDefaults.batchSize !== 1) {
throw new Error("tao-8k model supports only a batchSize of 1. Please adjust your batchSize accordingly");
}
this.batchSize = 1;
}
else {
this.batchSize = fieldsWithDefaults?.batchSize ?? this.batchSize;
}
this.stripNewLines =
fieldsWithDefaults?.stripNewLines ?? this.stripNewLines;
}
/**
* Method to generate embeddings for an array of documents. Splits the
* documents into batches and makes requests to the BaiduQianFan API to generate
* embeddings.
* @param texts Array of documents to generate embeddings for.
* @returns Promise that resolves to a 2D array of embeddings for each document.
*/
async embedDocuments(texts) {
const batches = (0, chunk_array_1.chunkArray)(this.stripNewLines ? texts.map((t) => t.replace(/\n/g, " ")) : texts, this.batchSize);
const batchRequests = batches.map((batch) => {
const params = this.getParams(batch);
return this.embeddingWithRetry(params);
});
const batchResponses = await Promise.all(batchRequests);
const embeddings = [];
for (let i = 0; i < batchResponses.length; i += 1) {
const batch = batches[i];
const batchResponse = batchResponses[i] || [];
for (let j = 0; j < batch.length; j += 1) {
embeddings.push(batchResponse[j]);
}
}
return embeddings;
}
/**
* Method to generate an embedding for a single document. Calls the
* embeddingWithRetry method with the document as the input.
* @param text Document to generate an embedding for.
* @returns Promise that resolves to an embedding for the document.
*/
async embedQuery(text) {
const params = this.getParams([
this.stripNewLines ? text.replace(/\n/g, " ") : text,
]);
const embeddings = (await this.embeddingWithRetry(params)) || [[]];
return embeddings[0];
}
/**
* Method to generate an embedding params.
* @param texts Array of documents to generate embeddings for.
* @returns an embedding params.
*/
getParams(texts) {
return {
input: texts,
};
}
/**
* Private method to make a request to the BaiduAI API to generate
* embeddings. Handles the retry logic and returns the response from the
* API.
* @param request Request to send to the BaiduAI API.
* @returns Promise that resolves to the response from the API.
*/
async embeddingWithRetry(body) {
if (!this.accessToken) {
this.accessToken = await this.getAccessToken();
}
return fetch(`https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/embeddings/${this.modelName}?access_token=${this.accessToken}`, {
method: "POST",
headers: {
"Content-Type": "application/json",
},
body: JSON.stringify(body),
}).then(async (response) => {
const embeddingData = await response.json();
if ("error_code" in embeddingData && embeddingData.error_code) {
throw new Error(`${embeddingData.error_code}: ${embeddingData.error_msg}`);
}
return embeddingData.data.map(({ embedding }) => embedding);
});
}
/**
* Method that retrieves the access token for making requests to the Baidu
* API.
* @returns The access token for making requests to the Baidu API.
*/
async getAccessToken() {
const url = `https://aip.baidubce.com/oauth/2.0/token?grant_type=client_credentials&client_id=${this.baiduApiKey}&client_secret=${this.baiduSecretKey}`;
const response = await fetch(url, {
method: "POST",
headers: {
"Content-Type": "application/json",
Accept: "application/json",
},
});
if (!response.ok) {
const text = await response.text();
const error = new Error(`Baidu get access token failed with status code ${response.status}, response: ${text}`);
// eslint-disable-next-line @typescript-eslint/no-explicit-any
error.response = response;
throw error;
}
const json = await response.json();
return json.access_token;
}
}
exports.BaiduQianfanEmbeddings = BaiduQianfanEmbeddings;